Uptake of systematic reviews and meta-analyses based on individual participant data in clinical practice guidelines: descriptive study.

To establish the extent to which systematic reviews and meta-analyses of individual participant data (IPD) are being used to inform the recommendations included in published clinical guidelines

Subgroup effects despite homogeneous heterogeneity test results

Background. Statistical tests of heterogeneity are very popular in meta-analyses, as heterogeneity might indicate subgroup effects. Lack of demonstrable statistical heterogeneity, however, might obscure clinical heterogeneity, meaning clinically relevant subgroup effects. Methods. A qualitative, visual method to explore the potential for subgroup effects was provided by a modification of the forest plot, i.e., adding a vertical axis indicating the proportion of a subgroup variable in the individual trials. Such a plot was used to assess the potential for clinically relevant subgroup effects and was illustrated by a clinical example on the effects of antibiotics in children with acute otitis media. Results. Statistical tests did not indicate heterogeneity in the meta-analysis on the effects of amoxicillin on acute otitis media (Q = 3.29, p = 0.51; I2 = 0%; T2 = 0). Nevertheless, in a modified forest plot, in which the individual trials were ordered by the proportion of children with bilateral otitis, a clear relation between bilaterality and treatment effects was observed (which was also found in an individual patient data meta-analysis of the included trials: p-value for interaction 0.021). Conclusions. A modification of the forest plot, by including an additional (vertical) axis indicating the proportion of a certain subgroup variable, is a qualitative, visual, and easy-to-interpret method to explore potential subgroup effects in studies included in meta-analyse

Two-Way Minimization: A Novel Treatment Allocation Method for Small Trials

Randomization is a hallmark of clinical trials. If a trial entails very few subjects and has many prognostic factors (or many factor levels) to be balanced, minimization is a more efficient method to achieve balance than a simple randomization. We propose a novel minimization method, the ‘two-way minimization’. The method separately calculates the ‘imbalance in the total numbers of subjects’ and the ‘imbalance in the distributions of prognostic factors’. And then to allocate a subject, it chooses—by probability—to minimize either one of these two aspects of imbalances. As such, it is a method that is both treatment-adaptive and covariate-adaptive. We perform Monte-Carlo simulations to examine its statistical properties. The two-way minimization (with proper regression adjustment of the force-balanced prognostic factors) has the correct type I error rates. It also produces point estimates that are unbiased and variance estimates that are accurate. When there are important prognostic factors to be balanced in the study, the method achieves the highest power and the smallest variance among randomization methods that are resistant to selection bias. The allocation can be done in real time and the subsequent data analysis is straightforward. The two-way minimization is recommended to balance prognostic factors in small trials

A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint.

Randomized trials typically estimate average relative treatment effects, but decisions on the benefit of a treatment are possibly better informed by more individualized predictions of the absolute treatment effect. In case of a binary outcome, these predictions of absolute individualized treatment effect require knowledge of the individual's risk without treatment and incorporation of a possibly differential treatment effect (ie, varying with patient characteristics). In this article, we lay out the causal structure of individualized treatment effect in terms of potential outcomes and describe the required assumptions that underlie a causal interpretation of its prediction. Subsequently, we describe regression models and model estimation techniques that can be used to move from average to more individualized treatment effect predictions. We focus mainly on logistic regression-based methods that are both well-known and naturally provide the required probabilistic estimates. We incorporate key components from both causal inference and prediction research to arrive at individualized treatment effect predictions. While the separate components are well known, their successful amalgamation is very much an ongoing field of research. We cut the problem down to its essentials in the setting of a randomized trial, discuss the importance of a clear definition of the estimand of interest, provide insight into the required assumptions, and give guidance with respect to modeling and estimation options. Simulated data illustrate the potential of different modeling options across scenarios that vary both average treatment effect and treatment effect heterogeneity. Two applied examples illustrate individualized treatment effect prediction in randomized trial data

Appointments, pay and performance in UK boardrooms by gender

This article uses UK data to examine issues regarding the scarcity of women in boardroom positions. The article examines appointments, pay and any associated productivity effects deriving from increased diversity. Evidence of gender-bias in the appointment of women as non-executive directors is found together with mixed evidence of discrimination in wages or fees paid. However, the article finds no support for the argument that gender diverse boards enhance corporate performance. Proposals in favour of greater board diversity may be best structured around the moral value of diversity, rather than with reference to an expectation of improved company performance

Burden of acute otitis media in primary care pediatrics in Italy: A secondary data analysis from the Pedianet database

Background: The incidence of acute otitis media (AOM) vary from country to country. Geographical variations together with differences in study designs, reporting and settings play a role. We assessed the incidence of AOM in Italian children seen by primary care paediatricians (PCPs), and described the methods used to diagnose the disease.Methods: This secondary data analysis from the Pedianet database considered children aged 0 - 6 years between 01/2003 and 12/2007. The AOM episodes were identified and validated by means of patient diaries. Incidence rates/100 person-years (PY) were calculated for total AOM and for single or recurrent AOM.Results: The 92,373 children (52.1% males) were followed up for a total of 227,361 PY: 23,039 (24.9%) presented 38,241 episodes of AOM (94.6% single episodes and 5.4% recurrent episodes). The total incidence rate of AOM in the 5-year period was 16.8 episodes per 100 PY (95% CI: 16.7-16.9), including single AOM (15.9 episodes per 100 PY; 95% CI: 15.7-16.1) and recurrent AOM (0.9 episodes per 100 PY; 95% CI: 0.9-0.9). There was a slight and continuously negative trend decrease over time (annual percent change -4.6%; 95%CI: -5.3, -3.9%). The AOM incidence rate varied with age, peaking in children aged 3 to 4 years (22.2 episodes per 100 PY; 95% CI 21.8-22.7). The vast majority of the AOM episodes (36,842/38,241, 96.3%) were diagnosed using a static otoscope; a pneumatic otoscope was used in only 3.7%.Conclusions: Our data fill a gap in our knowledge of the incidence of AOM in Italy, and indicate that AOM represents a considerable burden for the Italian PCP system. Educational programmes concerning the diagnosis of AOM are needed, as are further studies to monitor the incidence in relation to the introduction of wider pneumococcal conjugate vaccines

Traditional management of ear, nose and throat (ENT) diseases in Central Kenya

Diseases of ear, nose and throat (ENT) often have serious consequences including hearing impairment, and emotional strain that lower the quality of life of patients. In Kenya, upper respiratory infections are among the most common infections encountered in outpatient facilities. Some of these infections are becoming difficult to control because some of the causing microorganisms have acquired antibiotic resistance and hence the need to develop new drugs with higher efficacy. Ethnobotanical studies have now been found to be instrumental in improving chances of discovering plants with antimicrobial activity in new drug development. In Kenya the majority of local people are turning to herbal remedies for primary health care needs. In most cases the sources of these remedies are undocumented and the knowledge about them passed orally form generation to generation, hence under threat of disappearing with current rates of modernisation. This study explored the traditional remedies used in managing various ENT diseases in seven districts of the Central Province of Kenya. The most common ENT conditions managed using traditional therapies include: common cold, cough, tonsillitis, otitis-media, chest pains and asthma. The results indicate that 67 species belonging to 36 plant families were utilized in this region. These plants were of varying habits; herbs (37.3%), shrubs (34.4%), trees (25.4%) as well as some grasses and sedges (3%). The traditional preparations were found to be made mainly from leaves (49%), roots (20.5%) and barks (12.5%). For each of the ENT conditions multiple species are utilized mainly as individual preparations but occasionally as polyherbal concoctions. In the case of common cold for example, 30 different species are used. Plants reported in this survey are important candidates for antimicrobial tests against ENT disease causing micro-organisms, especially those with antibiotic resistance

Burden of Disease Caused by Otitis Media: Systematic Review and Global Estimates

<div><h3>Background</h3><p>Otitis media (OM) is a leading cause of health care visits and drugs prescription. Its complications and sequelae are important causes of preventable hearing loss, particularly in developing countries. Within the Global Burden of Diseases, Injuries, and Risk Factors Study, for the year 2005 we estimated the incidence of acute OM, chronic suppurative OM, and related hearing loss and mortality for all ages and the 21 WHO regional areas.</p> <h3>Methods</h3><p>We identified risk factors, complications and sequelae of OM. We carried out an extensive literature review (Medline, Embase, Lilacs and Wholis) which lead to the selection of 114 papers comprising relevant data. Data were available from 15 of the 21 WHO regions. To estimate incidence and prevalence for all countries we adopted a two stage approach based on risk factors formulas and regression modelling.</p> <h3>Results</h3><p>Acute OM incidence rate is 10.85% i.e. 709million cases each year with 51% of these occurring in under-fives. Chronic suppurative OM incidence rate is 4.76‰ i.e. 31million cases, with 22.6% of cases occurring annually in under-fives. OM-related hearing impairment has a prevalence of 30.82 per ten-thousand. Each year 21thousand people die due to complications of OM.</p> <h3>Conclusions</h3><p>Our study is the first attempt to systematically review the available information and provide global estimates for OM and related conditions. The overall burden deriving from AOM, CSOM and their sequelae is considerable, particularly in the first five years of life and in the poorest countries. The findings call for incorporating OM-focused action within preventive and case management strategies, with emphasis on the more affected.</p> </div